Level

CoreWeave

Staff Machine Learning Engineer, AI Insights

CoreWeave is hiring a Staff Machine Learning Engineer, AI Insights in New York, United States. It pays $180k-$250k a year and Level rates it ; you can apply on CoreWeave.

Level's read on this job

  • Builds AI ●●●● is how Level rates this machine learning engineer role: the job is building AI systems.
  • The posting mentions AI evaluation among its tools and skills.
  • Level classes it as a lead role.
  • CoreWeave has 315 other open roles on Level.

AI in this role

ai-evaluation
CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com.

About CoreWeave

CoreWeave is an AI hyperscaler building the cloud infrastructure and services that power the next generation of artificial intelligence. Our customers run demanding training, inference, and high-performance workloads, and our teams build the systems needed to operate that infrastructure reliably at scale.

About the team

The AI Insights team builds customer-facing AI capabilities across CoreWeave’s Mission Control portfolio. We combine machine learning, observability, and production software engineering to help engineers and customers understand workload health, diagnose infrastructure issues, and identify opportunities to improve efficiency, capacity, and performance.

Our work spans telemetry from metrics, logs, traces, alerts, and operational events. We are building the intelligence layer that turns this data into trustworthy, actionable insights—grounded in evidence and integrated into the tools where people operate CoreWeave infrastructure.

This is not a role focused on building a generic chatbot. You will help build the underlying ML systems, services, evaluation frameworks, and product capabilities that make AI-powered troubleshooting and optimization reliable in real-world environments.

About the role

As a Staff Machine Learning Engineer, you will be a technical leader on the AI Insights team. You will define and implement the machine learning systems that power anomaly detection, signal correlation, incident understanding, recommendations, and other intelligence capabilities across CoreWeave’s observability and cloud platforms.

You will work across the full lifecycle: framing problems, developing models and algorithms, designing evaluation methodology, building data and inference services, integrating with production systems, and operating the result at scale. You will partner closely with software engineers, product managers, researchers, and domain experts to turn promising ideas into reliable customer experiences.

What you’ll do

  • Lead the technical design and delivery of production machine learning systems for infrastructure observability, troubleshooting, and optimization.
  • Develop approaches for anomaly detection, time-series analysis, event correlation, ranking, recommendation, classification, and root-cause inference across high-volume telemetry.
  • Build evaluation frameworks and datasets that measure accuracy, usefulness, robustness, and safety in real operational scenarios.
  • Translate research and prototypes into maintainable, scalable services with clear operational ownership.
  • Design data pipelines, feature-generation workflows, model-serving paths, and feedback loops for continuous improvement.
  • Integrate ML capabilities with telemetry platforms and customer-facing experiences, including Mission Control, Grafana, and related observability services.
  • Establish practical standards for experimentation, offline and online evaluation, monitoring, reproducibility, and model lifecycle management.
  • Make thoughtful trade-offs across model quality, latency, cost, interpretability, reliability, and ease of operation.
  • Work with teams responsible for metrics, logs, traces, telemetry enrichment, and platform APIs to create coherent cross-system intelligence.
  • Mentor engineers and raise the technical bar for machine learning and production engineering across the organization.
  • Communicate technical decisions clearly and influence roadmaps across teams without relying on formal authority.

What we’re looking for

  • Significant experience designing and shipping machine learning systems that operate in production.
  • Strong software engineering skills in Python; experience with Go or another systems-oriented language is a plus.
  • Deep understanding of machine learning fundamentals, including model selection, feature engineering, experimentation, evaluation, and failure analysis.
  • Experience working with time-series, event, log, metric, trace, or other operational data at meaningful scale.
  • Demonstrated ability to define evaluation methodology for ambiguous or domain-specific ML problems.
  • Strong systems thinking and the ability to reason about distributed systems, data quality, latency, observability, and operational failure modes.
  • Excellent communication and collaboration skills, including the ability to work effectively with research, product, infrastructure, and customer-facing teams.
  • A track record of technical leadership, mentorship, and influence across organizational boundaries.

Nice to have

  • Experience with observability platforms or technologies such as Grafana, Prometheus, VictoriaMetrics, ClickHouse, Loki, or Kafka.
  • Experience with Kubernetes and cloud infrastructure, especially for telemetry, logging, or application observability.
  • Experience with anomaly detection, incident intelligence, search, recommendations, or ranking systems.
  • Experience with large language model evaluation, post-training, retrieval, tool use, or grounded generation—particularly when combined with structured telemetry and deterministic systems.
  • Experience building ML products for infrastructure, developer tools, reliability engineering, or other technical users.
  • Familiarity with human-in-the-loop workflows, access control, auditability, and safety requirements for operational systems.

Why this role

  • Work on foundational AI capabilities for an AI-native cloud company.
  • Solve difficult ML problems using high-volume, high-value infrastructure telemetry.
  • Help define how engineers and customers understand, troubleshoot, and optimize large-scale AI workloads.
  • Influence the technical direction of a growing team at the intersection of machine learning, observability, and distributed systems.
  • Turn applied research and engineering ideas into production products used by CoreWeave engineers and customers.
  • Lead by example while helping establish the team’s engineering and ML practices.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

  • Be Curious at Your Core
  • Act Like an Owner
  • Empower Employees
  • Deliver Best-in-Class Client Experiences
  • Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! 

The base salary range for this role is $180,000 to $250,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

What We Offer

The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.

In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include:

  • Medical, dental, and vision insurance - 100% paid for by CoreWeave
  • Company-paid Life Insurance 
  • Voluntary supplemental life insurance 
  • Short and long-term disability insurance 
  • Flexible Spending Account
  • Health Savings Account
  • Tuition Reimbursement 
  • Ability to Participate in Employee Stock Purchase Program (ESPP)
  • Mental Wellness Benefits through Spring Health 
  • Family-Forming support provided by Carrot
  • Paid Parental Leave 
  • Flexible, full-service childcare support with Kinside
  • 401(k) with a generous employer match
  • Flexible PTO
  • Catered lunch each day in our office and data center locations
  • A casual work environment
  • A work culture focused on innovative disruption

California Applicants

California Consumer Privacy Act 

Equal Opportunity & Accommodations

CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.

As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.

Export Control Compliance

This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency.  CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

How we rate this

Staff Machine Learning Engineer, AI Insights at CoreWeave rates 93 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI Evaluation

Also common in machine learning engineer jobs at this level

Pay

This job starts at
$180k
Typical machine learning engineer job
$199k

This posting starts 10% below the typical machine learning engineer job. See machine learning engineer jobs

Questions you could be asked

  1. How do you decide that one model's output is better than another's for a given task?
  2. How would you decide a model or AI system is ready to ship?
  3. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: AI Evaluation. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

Want an expert to read your CV for this job?

Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.

Get new machine learning engineer jobs (Builds AI ●●●●) by email

One email a week with the new machine learning engineer jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.

Free. One email a week. Unsubscribe in one click.

Similar roles

Data roles that build AI, at other companies.

What kind of AI work fits you?

Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.

Find my next step

More jobs at CoreWeave

More machine learning engineer jobs

Related searches

Same AI level

Jobs by city